Users of ASTER data have found Decorrelation Stretching to be particularly effective in image display. The stretch is effective whether the bands used are in the 

We also show the (intuitive) result that the optimum decorrelation of the of the myogenic response and stretch-induced calcium signaling in the vascular wall: 

Use decorrstretch to perform the decorrelation stretch. Specify the optional name-value pair 'Tol',0.1 to perform a linear contrast stretch after the decorrelation stretch. Performs a decorrelation stretch (transformation) on 2 to 256 channels of image data. This type of stretch is especially effective on images in which channels are highly correlated (that is, the spectral bands are very similar).

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A simple commmand line utility named process_image.py has been added to demonstrate the use of ds.py. Decorrelation methods seek to maximise the randomness of the phse between the two signals. This can be acheived using two mechanisms, phase based and amplitude based. Amplitude based decorrelation is where the input signal is divided between the output signals based on frequency i.e. even frequencies in the one output signal and odd frequencies in the second output signal. I want to perform a decorrelation stretch on the TIR bands 10,11 and 12 in IDL (so that the process is automated) .

30 May 2014 Left: plain view; right: after decorrelation stretch analysis digital enhancement.

Decorrelation stretching is a way to enhance the color differences in an image. The primary purpose of decorrelation stretch is visual enhancement. Como se 

This is generally termed as 'decorrelation stretching'. and reading from right to left, you can see that the decorrelation stretch: Removes a mean from each band Normalizes each band by its standard deviation (correlation-based method only) Rotates the bands into the eigenspace of Corr or Cov Applies a stretch S in the eigenspace, leaving the image Decorrelation Stretch If the data are transformed into principal components space and are stretched within this space, then the three bands making up the RGB colour composite images are subjected to stretch will be at the right angles to each other. Decorrelation stretch, an image enhancement technique first used in remote sensing, can be usefully applied to rock art.

Decorrelation stretch is used to enhance color differences in images with high interchannel correlation. Therefore it allows us to see details that are otherwise not so obvious or invisible to the human eye. I first came across decorrelation stretch in a Matlab webinar and was curious to find out how it works.

Decorrelation Stretch, like principal component analysis, can be based on the covariance matrix or the correlation matrix, the resultant value of the decorrelation stretch is also a function of the nature of the image to which it is applied. A direct decorrelation stretch of a RGB colour image is achieved by decreasing the magnitude of the achromatic component of the colour vector for the pixel being processed. Initially, the R, G, and B digital numbers (DNs) for each colour pixel are examined and the lowest value (it could be the red, green or blue) is selected.

Spatial decorrelation stretch of annual (2003-2014) Daymet precipitation summaries on a 1-km grid for California, Nevada, Arizona, and Utah. Ch Miliaresis G(1). Author information: (1)Environmental Conservation & Management, Faculty of Pure and Applied Sciences, Open University of Cyprus, 38, Tripoleos Str., 104-42, Athens, Greece. gmiliar@yahoo.com. Decorrelation stretch in Python. Contribute to lbrabec/decorrstretch development by creating an account on GitHub. Performs a decorrelation stretch (transformation) on 2 to 256 channels of image data.
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Initially, the R, G, and B digital numbers (DNs) for each colour pixel are examined and the lowest value (it could be the red, green or blue) is selected. The decorrelation stretch analysis produces a 3x3 numeric matrix as an end result that specifies the color transformation to be performed. In DStretch this result can be stored and reused on other images, skipping the decorrelation stretch analysis. Some matrices have turned out to be generally useful and have been built into the program.

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IHS_Decorrelation_Stretch_v16_6_1.gmdx In the provided model the user specifies which three bands represent data that is usually displayed as an RGB color composite. For true color aerial photography this would normally be 1,2,3, but may vary for other sensors.

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